



import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE__   			=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   			=   '''▁'''

SCREAMING_SNAKE_CASE__   			=   {'''vocab_file''': '''sentencepiece.bpe.model'''}

SCREAMING_SNAKE_CASE__   			=   {
    '''vocab_file''': {
        '''facebook/nllb-200-distilled-600M''': (
            '''https://huggingface.co/facebook/nllb-200-distilled-600M/blob/main/sentencepiece.bpe.model'''
        ),
    }
}

SCREAMING_SNAKE_CASE__   			=   {
    '''facebook/nllb-200-distilled-600M''': 1_0_2_4,
}

# fmt: off
SCREAMING_SNAKE_CASE__   			=   ['''ace_Arab''', '''ace_Latn''', '''acm_Arab''', '''acq_Arab''', '''aeb_Arab''', '''afr_Latn''', '''ajp_Arab''', '''aka_Latn''', '''amh_Ethi''', '''apc_Arab''', '''arb_Arab''', '''ars_Arab''', '''ary_Arab''', '''arz_Arab''', '''asm_Beng''', '''ast_Latn''', '''awa_Deva''', '''ayr_Latn''', '''azb_Arab''', '''azj_Latn''', '''bak_Cyrl''', '''bam_Latn''', '''ban_Latn''', '''bel_Cyrl''', '''bem_Latn''', '''ben_Beng''', '''bho_Deva''', '''bjn_Arab''', '''bjn_Latn''', '''bod_Tibt''', '''bos_Latn''', '''bug_Latn''', '''bul_Cyrl''', '''cat_Latn''', '''ceb_Latn''', '''ces_Latn''', '''cjk_Latn''', '''ckb_Arab''', '''crh_Latn''', '''cym_Latn''', '''dan_Latn''', '''deu_Latn''', '''dik_Latn''', '''dyu_Latn''', '''dzo_Tibt''', '''ell_Grek''', '''eng_Latn''', '''epo_Latn''', '''est_Latn''', '''eus_Latn''', '''ewe_Latn''', '''fao_Latn''', '''pes_Arab''', '''fij_Latn''', '''fin_Latn''', '''fon_Latn''', '''fra_Latn''', '''fur_Latn''', '''fuv_Latn''', '''gla_Latn''', '''gle_Latn''', '''glg_Latn''', '''grn_Latn''', '''guj_Gujr''', '''hat_Latn''', '''hau_Latn''', '''heb_Hebr''', '''hin_Deva''', '''hne_Deva''', '''hrv_Latn''', '''hun_Latn''', '''hye_Armn''', '''ibo_Latn''', '''ilo_Latn''', '''ind_Latn''', '''isl_Latn''', '''ita_Latn''', '''jav_Latn''', '''jpn_Jpan''', '''kab_Latn''', '''kac_Latn''', '''kam_Latn''', '''kan_Knda''', '''kas_Arab''', '''kas_Deva''', '''kat_Geor''', '''knc_Arab''', '''knc_Latn''', '''kaz_Cyrl''', '''kbp_Latn''', '''kea_Latn''', '''khm_Khmr''', '''kik_Latn''', '''kin_Latn''', '''kir_Cyrl''', '''kmb_Latn''', '''kon_Latn''', '''kor_Hang''', '''kmr_Latn''', '''lao_Laoo''', '''lvs_Latn''', '''lij_Latn''', '''lim_Latn''', '''lin_Latn''', '''lit_Latn''', '''lmo_Latn''', '''ltg_Latn''', '''ltz_Latn''', '''lua_Latn''', '''lug_Latn''', '''luo_Latn''', '''lus_Latn''', '''mag_Deva''', '''mai_Deva''', '''mal_Mlym''', '''mar_Deva''', '''min_Latn''', '''mkd_Cyrl''', '''plt_Latn''', '''mlt_Latn''', '''mni_Beng''', '''khk_Cyrl''', '''mos_Latn''', '''mri_Latn''', '''zsm_Latn''', '''mya_Mymr''', '''nld_Latn''', '''nno_Latn''', '''nob_Latn''', '''npi_Deva''', '''nso_Latn''', '''nus_Latn''', '''nya_Latn''', '''oci_Latn''', '''gaz_Latn''', '''ory_Orya''', '''pag_Latn''', '''pan_Guru''', '''pap_Latn''', '''pol_Latn''', '''por_Latn''', '''prs_Arab''', '''pbt_Arab''', '''quy_Latn''', '''ron_Latn''', '''run_Latn''', '''rus_Cyrl''', '''sag_Latn''', '''san_Deva''', '''sat_Beng''', '''scn_Latn''', '''shn_Mymr''', '''sin_Sinh''', '''slk_Latn''', '''slv_Latn''', '''smo_Latn''', '''sna_Latn''', '''snd_Arab''', '''som_Latn''', '''sot_Latn''', '''spa_Latn''', '''als_Latn''', '''srd_Latn''', '''srp_Cyrl''', '''ssw_Latn''', '''sun_Latn''', '''swe_Latn''', '''swh_Latn''', '''szl_Latn''', '''tam_Taml''', '''tat_Cyrl''', '''tel_Telu''', '''tgk_Cyrl''', '''tgl_Latn''', '''tha_Thai''', '''tir_Ethi''', '''taq_Latn''', '''taq_Tfng''', '''tpi_Latn''', '''tsn_Latn''', '''tso_Latn''', '''tuk_Latn''', '''tum_Latn''', '''tur_Latn''', '''twi_Latn''', '''tzm_Tfng''', '''uig_Arab''', '''ukr_Cyrl''', '''umb_Latn''', '''urd_Arab''', '''uzn_Latn''', '''vec_Latn''', '''vie_Latn''', '''war_Latn''', '''wol_Latn''', '''xho_Latn''', '''ydd_Hebr''', '''yor_Latn''', '''yue_Hant''', '''zho_Hans''', '''zho_Hant''', '''zul_Latn''']


class   __lowerCAmelCase  (		_lowerCAmelCase   ):
					"""simple docstring"""






					A__					:		List[Any]      							=     VOCAB_FILES_NAMES
					A__					:		Any      							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A__					:		Any      							=     PRETRAINED_VOCAB_FILES_MAP
					A__					:		str      							=     ['''input_ids''', '''attention_mask''']

					A__					:		List[int]      							=     []
					A__					:		List[int]      							=     []



					def __init__(  self       :							str					,       _snake_case       :							List[Any]					,       _snake_case       :							List[str]="<s>"					,       _snake_case       :							List[str]="</s>"					,       _snake_case       :							List[str]="</s>"					,       _snake_case       :							Union[str, Any]="<s>"					,       _snake_case       :							Dict="<unk>"					,       _snake_case       :							Optional[Any]="<pad>"					,       _snake_case       :							List[Any]="<mask>"					,       _snake_case       :							Union[str, Any]=None					,       _snake_case       :							Tuple=None					,       _snake_case       :							List[str]=None					,       _snake_case       :							Optional[Dict[str, Any]] = None					,       _snake_case       :							Optional[int]=None					,       _snake_case       :							List[str]=False					,       **_snake_case       :							Optional[int]					,       ):






								"""simple docstring"""


								A__	  =     AddedToken(UpperCAmelCase_					,       lstrip=UpperCAmelCase_					,       rstrip=UpperCAmelCase_       ) if isinstance(UpperCAmelCase_					,       UpperCAmelCase_       ) else mask_token

								A__	  =     {} if sp_model_kwargs is None else sp_model_kwargs
								A__	  =     legacy_behaviour

								super().__init__(
								    bos_token=UpperCAmelCase_					,       eos_token=UpperCAmelCase_					,       unk_token=UpperCAmelCase_					,       sep_token=UpperCAmelCase_					,       cls_token=UpperCAmelCase_					,       pad_token=UpperCAmelCase_					,       mask_token=UpperCAmelCase_					,       tokenizer_file=UpperCAmelCase_					,       src_lang=UpperCAmelCase_					,       tgt_lang=UpperCAmelCase_					,       additional_special_tokens=UpperCAmelCase_					,       sp_model_kwargs=self.sp_model_kwargs					,       legacy_behaviour=UpperCAmelCase_					,       **UpperCAmelCase_					,       )

								A__	  =     spm.SentencePieceProcessor(**self.sp_model_kwargs       )
								self.sp_model.Load(str(UpperCAmelCase_       )       )
								A__	  =     vocab_file
								# Original fairseq vocab and spm vocab must be "aligned":
								# Vocab    |    0    |    1    |   2    |    3    |  4   |  5   |  6   |   7  |   8  |  9
								# -------- | ------- | ------- | ------ | ------- | ---- | ---- | ---- | ---- | ---- | ----
								# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | 'an' | '▁n' | '▁m' | '▁t' | '▁k' | '▁a'
								# spm      | '<unk>' | '<s>'   | '</s>' | 'an'    | '▁n' | '▁m' | '▁t' | '▁k' | '▁a' | '▁s'

								# Mimic fairseq token-to-id alignment for the first 4 token
								A__	  =     {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

								# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
								A__	  =     1

								A__	  =     len(self.sp_model       )
								A__	  =     {
								    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(UpperCAmelCase_       )
								}
								A__	  =     {v: k for k, v in self.lang_code_to_id.items()}
								A__	  =     len(self.sp_model       ) + len(self.lang_code_to_id       ) + self.fairseq_offset

								self.fairseq_tokens_to_ids.update(self.lang_code_to_id       )
								A__	  =     {v: k for k, v in self.fairseq_tokens_to_ids.items()}
								A__	  =     list(self.lang_code_to_id.keys()       )

								if additional_special_tokens is not None:
											# Only add those special tokens if they are not already there.
											self._additional_special_tokens.extend(
											    [t for t in additional_special_tokens if t not in self._additional_special_tokens]       )

								A__	  =     src_lang if src_lang is not None else 'eng_Latn'
								A__	  =     self.lang_code_to_id[self._src_lang]
								A__	  =     tgt_lang
								self.set_src_lang_special_tokens(self._src_lang       )



					def __getstate__(  self       :							List[Any]       ):






								"""simple docstring"""


								A__	  =     self.__dict__.copy()
								A__	  =     None
								A__	  =     self.sp_model.serialized_model_proto()
								return state



					def __setstate__(  self       :							int					,       _snake_case       :							Tuple       ):






								"""simple docstring"""


								A__	  =     d

								# for backward compatibility
								if not hasattr(self					,       'sp_model_kwargs'       ):
											A__	  =     {}

								A__	  =     spm.SentencePieceProcessor(**self.sp_model_kwargs       )
								self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )



					@property
					def      _a				(  self       :							Dict       ):






								"""simple docstring"""


								return len(self.sp_model       ) + len(self.lang_code_to_id       ) + self.fairseq_offset + 1  # Plus 1 for the mask token



					@property
					def      _a				(  self       :							Optional[int]       ):






								"""simple docstring"""


								return self._src_lang



					@src_lang.setter
					def      _a				(  self       :							int					,       _snake_case       :							str       ):






								"""simple docstring"""


								A__	  =     new_src_lang
								self.set_src_lang_special_tokens(self._src_lang       )



					def      _a				(  self       :							Tuple					,       _snake_case       :							List[int]					,       _snake_case       :							Optional[List[int]] = None					,       _snake_case       :							bool = False       ):






								"""simple docstring"""


								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=UpperCAmelCase_					,       token_ids_a=UpperCAmelCase_					,       already_has_special_tokens=UpperCAmelCase_       )

								A__	  =     [1] * len(self.prefix_tokens       )
								A__	  =     [1] * len(self.suffix_tokens       )
								if token_ids_a is None:
											return prefix_ones + ([0] * len(UpperCAmelCase_       )) + suffix_ones
								return prefix_ones + ([0] * len(UpperCAmelCase_       )) + ([0] * len(UpperCAmelCase_       )) + suffix_ones



					def      _a				(  self       :							List[str]					,       _snake_case       :							List[int]					,       _snake_case       :							Optional[List[int]] = None       ):






								"""simple docstring"""


								if token_ids_a is None:
											return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens



					def      _a				(  self       :							Dict					,       _snake_case       :							List[int]					,       _snake_case       :							Optional[List[int]] = None       ):






								"""simple docstring"""


								A__	  =     [self.sep_token_id]
								A__	  =     [self.cls_token_id]

								if token_ids_a is None:
											return len(cls + token_ids_a + sep       ) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]



					def      _a				(  self       :							Optional[Any]					,       _snake_case       :							Any					,       _snake_case       :							str					,       _snake_case       :							Optional[str]					,       _snake_case       :							Optional[str]					,       **_snake_case       :							Tuple       ):






								"""simple docstring"""


								if src_lang is None or tgt_lang is None:
											raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'       )
								A__	  =     src_lang
								A__	  =     self(UpperCAmelCase_					,       add_special_tokens=UpperCAmelCase_					,       return_tensors=UpperCAmelCase_					,       **UpperCAmelCase_       )
								A__	  =     self.convert_tokens_to_ids(UpperCAmelCase_       )
								A__	  =     tgt_lang_id
								return inputs



					def      _a				(  self       :							Dict       ):






								"""simple docstring"""


								A__	  =     {self.convert_ids_to_tokens(UpperCAmelCase_       ): i for i in range(self.vocab_size       )}
								vocab.update(self.added_tokens_encoder       )
								return vocab



					def      _a				(  self       :							str					,       _snake_case       :							str       ):






								"""simple docstring"""


								return self.sp_model.encode(UpperCAmelCase_					,       out_type=UpperCAmelCase_       )



					def      _a				(  self       :							Optional[Any]					,       _snake_case       :							Union[str, Any]       ):






								"""simple docstring"""


								if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
								A__	  =     self.sp_model.PieceToId(UpperCAmelCase_       )

								# Need to return unknown token if the SP model returned 0
								return spm_id + self.fairseq_offset if spm_id else self.unk_token_id



					def      _a				(  self       :							int					,       _snake_case       :							str       ):






								"""simple docstring"""


								if index in self.fairseq_ids_to_tokens:
											return self.fairseq_ids_to_tokens[index]
								return self.sp_model.IdToPiece(index - self.fairseq_offset       )



					def      _a				(  self       :							Any					,       _snake_case       :							List[Any]       ):






								"""simple docstring"""


								A__	  =     ''.join(UpperCAmelCase_       ).replace(UpperCAmelCase_					,       ' '       ).strip()
								return out_string



					def      _a				(  self       :							str					,       _snake_case       :							str					,       _snake_case       :							Optional[str] = None       ):






								"""simple docstring"""


								if not os.path.isdir(UpperCAmelCase_       ):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''       )
											return
								A__	  =     os.path.join(
								    UpperCAmelCase_					,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )

								if os.path.abspath(self.vocab_file       ) != os.path.abspath(UpperCAmelCase_       ) and os.path.isfile(self.vocab_file       ):
											copyfile(self.vocab_file					,       UpperCAmelCase_       )
								elif not os.path.isfile(self.vocab_file       ):
											with open(UpperCAmelCase_					,       'wb'       ) as fi:
														A__	  =     self.sp_model.serialized_model_proto()
														fi.write(UpperCAmelCase_       )

								return (out_vocab_file,)



					def      _a				(  self       :							Optional[int]					,       _snake_case       :							List[str]					,       _snake_case       :							str = "eng_Latn"					,       _snake_case       :							Optional[List[str]] = None					,       _snake_case       :							str = "fra_Latn"					,       **_snake_case       :							Tuple					,       ):






								"""simple docstring"""


								A__	  =     src_lang
								A__	  =     tgt_lang
								return super().prepare_seqaseq_batch(UpperCAmelCase_					,       UpperCAmelCase_					,       **UpperCAmelCase_       )



					def      _a				(  self       :							str       ):






								"""simple docstring"""


								return self.set_src_lang_special_tokens(self.src_lang       )



					def      _a				(  self       :							Union[str, Any]       ):






								"""simple docstring"""


								return self.set_tgt_lang_special_tokens(self.tgt_lang       )



					def      _a				(  self       :							Any					,       _snake_case       :							int       ):






								"""simple docstring"""


								A__	  =     self.lang_code_to_id[src_lang]
								if self.legacy_behaviour:
											A__	  =     []
											A__	  =     [self.eos_token_id, self.cur_lang_code]
								else:
											A__	  =     [self.cur_lang_code]
											A__	  =     [self.eos_token_id]



					def      _a				(  self       :							Optional[int]					,       _snake_case       :							str       ):






								"""simple docstring"""


								A__	  =     self.lang_code_to_id[lang]
								if self.legacy_behaviour:
											A__	  =     []
											A__	  =     [self.eos_token_id, self.cur_lang_code]
								else:
											A__	  =     [self.cur_lang_code]
											A__	  =     [self.eos_token_id]






"""simple docstring"""


import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_=7					)->				Optional[Any]:







       """simple docstring"""
       UpperCamelCase       			=		None
       if token is not None:
              UpperCamelCase       			=		{"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

       # The id of a workflow (not of a workflow run)
       UpperCamelCase       			=		"636036"

       UpperCamelCase       			=		F"https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"
       # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
       url += F"?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"

       UpperCamelCase       			=		requests.get(UpperCAmelCase_		,   headers=UpperCAmelCase_					).json()

       return result["workflow_runs"]



def 						lowerCamelCase__      (				UpperCAmelCase_					)->				Any:







       """simple docstring"""
       UpperCamelCase       			=		get_daily_ci_runs(UpperCAmelCase_					)
       UpperCamelCase       			=		None
       for workflow_run in workflow_runs:
              if workflow_run["status"] == "completed":
                     UpperCamelCase       			=		workflow_run["id"]
                     break

       return workflow_run_id



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				int:







       """simple docstring"""
       UpperCamelCase       			=		get_last_daily_ci_runs(UpperCAmelCase_					)
       if workflow_run_id is not None:
              UpperCamelCase       			=		get_artifacts_links(worflow_run_id=UpperCAmelCase_		,   token=UpperCAmelCase_					)
              for artifact_name in artifact_names:
                     if artifact_name in artifacts_links:
                            UpperCamelCase       			=		artifacts_links[artifact_name]
                            download_artifact(
                                artifact_name=UpperCAmelCase_		,   artifact_url=UpperCAmelCase_		,   output_dir=UpperCAmelCase_		,   token=UpperCAmelCase_					)



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				Optional[int]:







       """simple docstring"""
       get_last_daily_ci_artifacts(UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)

       UpperCamelCase       			=		{}
       for artifact_name in artifact_names:
              UpperCamelCase       			=		os.path.join(UpperCAmelCase_		,   F"{artifact_name}.zip"					)
              if os.path.isfile(UpperCAmelCase_					):
                     UpperCamelCase       			=		{}
                     with zipfile.ZipFile(UpperCAmelCase_					) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(UpperCAmelCase_					):
                                          # read the file
                                          with z.open(UpperCAmelCase_					) as f:
                                                 UpperCamelCase       			=		f.read().decode("UTF-8"					)

       return results





